journal-of-statistics-and-management-systems Journal of Statistics and Management Systems 2169-0014 0972-0510 Taru Publications 10.47974/JSMS-1377 An adaptive run sum scheme for process ratio Abubakar Sani Salihu Department of Statistics, Aliko Dangote University of Science and Technology, Wudil, 713101, Nigeria Khoo Michael B. C. School of Mathematical Sciences, Universiti Sains Malaysia, Penang, 11800, Malaysia Mim Faijun Nahar Department of Statistics, Mawlana Bhashani Science and Technology University, Tangail, 1902, Bangladesh Umar Adamu Abubakar Department of Statistics, Faculty of Physical Sciences, Ahmadu Bello University, Zaria – Kaduna, 810222, Nigeria Yeong Wai Chung Faculty of Computing and Informatics, Persiaran Multimedia, Multimedia University, Cyberjaya, 63100, Malaysia Abdullahi Ibrahim Department of Mathematics and Statistics, School of Mathematics and Computing, Kampala International University, 20000, Uganda 28 3 505 534 08 04 2025

Tracking the ratio of two normal variables (RTNV) is crucial in ensuring the quality regarding some manufacturing processes. In this study, the run sum and variable sampling interval procedures are combined to develop a more effective scheme for controlling the RTNV A comparison with the existing basic ratio and run sum ratio schemes, as per average time to signal criterion, shows that the new chart substantially surpasses its two existing counterparts. An example of application using factual data is given to showcase the operation of the new scheme in practice.

 Variable sampling interval Run sum ratio scheme Distribution of the ratio statistic Markov chain Average time to signal access open retracted no